Instructions to use hf-tiny-model-private/tiny-random-TableTransformerForObjectDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-TableTransformerForObjectDetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="hf-tiny-model-private/tiny-random-TableTransformerForObjectDetection")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-TableTransformerForObjectDetection") model = AutoModelForObjectDetection.from_pretrained("hf-tiny-model-private/tiny-random-TableTransformerForObjectDetection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 15f00a48235e4169286fd6fb3d66255313a39c4135544512e4b285d59da754b4
- Size of remote file:
- 103 MB
- SHA256:
- 524f004f2f85a44c945d663f9d7bd3c253860e7046922ade69c9414d7395c965
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